Reasoning
Like-for-like- GPT-5.2
- 52.9
- Grok 4.5
- 52.6
- Weighted basis
- 1 vs 1 rows
- Reading
- GPT-5.2 leads
GPT-5.2 vs Grok 4.5
Updated August 22, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.
Decision reading
Grok 4.5 has the higher public score, 75.19 versus 57.96, and the 90% score intervals do not overlap.
2 results are shared. Category rows based on different benchmark sets are marked directional and do not name a winner.
Which one for your work
Recommendations appear only when a shared evidence basis or an explicit operating constraint supports the call. Secondary and unsupported use cases stay disclosed below the initial list.
Long documents
Prompts that approach the documented context limit
Grok 4.5
Grok 4.5 has the larger documented context window.
Confidence: documented
Chat turn cost
1K fresh input + 500 output tokens
Grok 4.5
Grok 4.5 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
Cache-heavy agent loop cost
200K cached + 20K fresh input + 10K output tokens
Grok 4.5
Grok 4.5 has the lower estimated token cost for this stated workload. GPT-5.2 has no published cached-input rate, so cached tokens use its listed input rate.
Confidence: rate-fallback
Show secondary and unsupported calls
Repository review cost
50K fresh input + 3K output tokens
Grok 4.5
Grok 4.5 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
Coding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
The category averages use different weighted benchmark sets, so they are directional rather than like-for-like.
Confidence: limited
Agentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
No shared weighted benchmark basis supports a winner.
Confidence: limited
What is actually comparable
Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.
13 GPT-5.2 only
2 Shared
8 Grok 4.5 only
- Shared results
- 2
- GPT-5.2 only
- 13
- Grok 4.5 only
- 8
- Like-for-like categories
- 1 / 8
1 category uses different evidence sets. Those rows remain visible for coverage context but do not name a winner.
Category results, on a stated basis
Each row states whether both averages use the same weighted benchmark set. Directional and not-comparable rows remain visible, but they never receive a winner in this template.
Coding
Directional only- GPT-5.2
- 70.6
- Grok 4.5
- 64.7
- Weighted basis
- 2 vs 1 rows
- Reading
- Directional only
Agentic
Not comparable- GPT-5.2
- 55.7
- Grok 4.5
- 83.3
- Weighted basis
- 2 vs 1 rows
- Reading
- Not comparable
Knowledge
Not comparable- GPT-5.2
- 92.4
- Grok 4.5
- Not measured
- Weighted basis
- 1 vs 0 rows
- Reading
- Not comparable
Math
Not comparable- GPT-5.2
- 35.2
- Grok 4.5
- Not measured
- Weighted basis
- 2 vs 0 rows
- Reading
- Not comparable
Multilingual
Not comparable- GPT-5.2
- Not measured
- Grok 4.5
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
Multimodal
Not comparable- GPT-5.2
- 80.4
- Grok 4.5
- Not measured
- Weighted basis
- 2 vs 0 rows
- Reading
- Not comparable
Instruction following
Not comparable- GPT-5.2
- Not measured
- Grok 4.5
- Not measured
- Weighted basis
- 0 vs 0 rows
- Reading
- Not comparable
| Category | GPT-5.2 | Grok 4.5 | Weighted basis | Reading |
|---|---|---|---|---|
| Reasoning | 52.9 | 52.6 | Like-for-like1 vs 1 rows | GPT-5.2 leads |
| Coding | 70.6 | 64.7 | Directional only2 vs 1 rows | Directional only |
| Agentic | 55.7 | 83.3 | Not comparable2 vs 1 rows | Not comparable |
| Knowledge | 92.4 | Not measured | Not comparable1 vs 0 rows | Not comparable |
| Math | 35.2 | Not measured | Not comparable2 vs 0 rows | Not comparable |
| Multilingual | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
| Multimodal | 80.4 | Not measured | Not comparable2 vs 0 rows | Not comparable |
| Instruction following | Not measured | Not measured | Not comparable0 vs 0 rows | Not comparable |
Shape of the matched evidence
Only shared public evidence is shown. Sparse evidence stays a ruled list rather than being closed into a radar shape.
Too few matched category axes support a radar. The ruled list below shows only shared benchmark results; positions use each benchmark’s normalized display scale when available.
SWE-bench Pro
Coding
ARC-AGI-2
Reasoning
What each workload costs
Three fixed token mixes turn per-token rates into comparable decisions. Each scenario states context fit and whether cached input had to fall back to the published list-input rate.
Chat turn
1K fresh input + 500 output tokens
- GPT-5.2
- $0.00875
- Fits in one request
- Grok 4.5
- $0.005
- Fits in one request
Grok 4.5 has the lower modeled cost
Costs use the listed standard API rates.
Repository review
50K fresh input + 3K output tokens
- GPT-5.2
- $0.1295
- Fits in one request
- Grok 4.5
- $0.118
- Fits in one request
Grok 4.5 has the lower modeled cost
Costs use the listed standard API rates.
Cache-heavy agent loop
200K cached + 20K fresh input + 10K output tokens
- GPT-5.2
- $0.525
- Fits in one request
- Cached input priced at the published list-input rate
- Grok 4.5
- $0.16
- Fits in one request
Grok 4.5 has the lower modeled cost
GPT-5.2 has no published cached-input rate, so cached tokens use its listed input rate.
Specification differences
Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.
SpecificationGPT-5.2Grok 4.5
Context window
Maximum documented context; output-token limits may be lower.
GPT-5.2
400K
Grok 4.5
500K
API model ID
GPT-5.2
Not sourced
Grok 4.5
Not sourced
Cached-input rate
A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.
GPT-5.2
Not published
Grok 4.5
$0.3 per 1M cached input tokens
Documented inputs
GPT-5.2
Not sourced
Grok 4.5
Not sourced
Documented outputs
GPT-5.2
Not sourced
Grok 4.5
Not sourced
Provider availability
GPT-5.2
Not sourced
Grok 4.5
Not sourced
Reasoning profile
GPT-5.2
Reasoning
Grok 4.5
Reasoning
Weight access
GPT-5.2
Proprietary
Grok 4.5
Proprietary
License
GPT-5.2
Proprietary
Grok 4.5
Proprietary
Release date
GPT-5.2
2025-12-11
Grok 4.5
2026-07-08
If you already use one of these models
- Deployment change
- The models list different providers, so authentication, endpoint behavior, limits, and feature support may change.
- Quality signal
- Grok 4.5 has the higher public score, 75.19 versus 57.96, and the 90% score intervals do not overlap.
- Workload cost
- Repository review: $0.1295 vs $0.118. Cache-heavy agent loop: $0.525 vs $0.16.
- Context tradeoff
- Grok 4.5 has the larger documented window (500K).
Run the same representative tasks against both endpoints before changing production traffic.
Benchmark evidence
The full public result ledger is available for audit without forcing a wide desktop table onto a phone.
Browse raw public benchmark evidence23 rows
Agentic
BrowseComp
GPT-5.265.8%SourceGrok 4.5—Not directly comparable
OSWorld-Verified
GPT-5.247.3%SourceGrok 4.5—Not directly comparable
Gert Labs
GPT-5.246.54%SourceGrok 4.5—Not directly comparable
JobBench
GPT-5.234.3%SourceGrok 4.5—Not directly comparable
Terminal-Bench 3.0
GPT-5.2—Grok 4.515.7%SourceNot directly comparable
Terminal-Bench 2.0
GPT-5.2—Grok 4.583.3%SourceNot directly comparable
deepSwe
GPT-5.2—Grok 4.553%SourceNot directly comparable
Coding
SWE-bench Verified
GPT-5.280%SourceGrok 4.5—Not directly comparable
SWE-bench Pro
GPT-5.255.6%SourceGrok 4.564.7%SourceGrok 4.5 leads this result
Vibe Code Bench
GPT-5.253.50%SourceGrok 4.5—Not directly comparable
SWE Multilingual
GPT-5.2—Grok 4.578%SourceNot directly comparable
Terminal-Bench 2.0
GPT-5.2—Grok 4.583.3%SourceNot directly comparable
cursorBench32
GPT-5.2—Grok 4.566.7%SourceNot directly comparable
VulcanBench v3
GPT-5.2—Grok 4.591.3%SourceNot directly comparable
Reasoning
Knowledge
GPQA
GPT-5.292.4%SourceGrok 4.5—Not directly comparable
Math
Multimodal
Frequently asked questions
Which is better, GPT-5.2 or Grok 4.5?
Grok 4.5 has the higher public score, 75.19 versus 57.96, and the 90% score intervals do not overlap. That is the clearest overall quality signal in the current public data.
Which is better for coding, GPT-5.2 or Grok 4.5?
The current coding averages use different weighted benchmark sets, so BenchLM does not name a winner from them. Read the shared benchmark rows directly and test the models on the same task set.
Which is better for agentic tasks, GPT-5.2 or Grok 4.5?
The published evidence does not provide a shared weighted agentic tasks basis for both models, so BenchLM does not name a agentic tasks winner.
Which costs less, GPT-5.2 or Grok 4.5?
For the stated presets, chat costs $0.00875 on GPT-5.2 and $0.005 on Grok 4.5; repository review costs $0.1295 and $0.118; the cache-heavy agent loop costs $0.525 and $0.16. GPT-5.2 has no published cached-input rate, so cached tokens use its listed input rate.
Which has the larger context window, GPT-5.2 or Grok 4.5?
Grok 4.5 has the larger documented context window: 500K, compared with 400K.
Related comparisons
Last updated August 22, 2026
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